Tips for building a Twitter bot with R and Github Actions {https://t.co/FTrKW1S0zL} #rstats #DataScience
— R-bloggers (@Rbloggers) January 16, 2022
The Basics of R (in Spanish!) {https://t.co/lR4IiiVZgL} #rstats #DataScience
— R-bloggers (@Rbloggers) January 20, 2022
Detecting multicollinearity — it’s not that easy sometimes {https://t.co/4HXPQw5Bhi} #rstats #DataScience
— R-bloggers (@Rbloggers) January 21, 2022
Playing Wordle in R {https://t.co/J1IxF5L5kT} #rstats #DataScience
— R-bloggers (@Rbloggers) January 18, 2022
Systematic Sampling in R with example {https://t.co/PuwDKXT9ii} #rstats #DataScience
— R-bloggers (@Rbloggers) January 18, 2022
Understanding the native R pipe |> {https://t.co/JodmFZGn72} #rstats #DataScience
— R-bloggers (@Rbloggers) January 19, 2022
Chi-Square Goodness of fit formula in R {https://t.co/P2RsEsYquJ} #rstats #DataScience
— R-bloggers (@Rbloggers) January 18, 2022
Time Series Forecasting Lab (Part 6) – Stacked Ensembles {https://t.co/0nhtRjbsqF} #rstats #DataScience
— R-bloggers (@Rbloggers) January 21, 2022
Understanding Lasso and Ridge Regression {https://t.co/NlI2AlEXsx} #rstats #DataScience
— R-bloggers (@Rbloggers) January 21, 2022
Showcasing the janitor package {https://t.co/tZbykIJ6Xp} #rstats #DataScience
— R-bloggers (@Rbloggers) January 21, 2022
{emayili} Sending Email from Shiny {https://t.co/w0v49LMDxn} #rstats #DataScience
— R-bloggers (@Rbloggers) January 20, 2022
Programmatically create new headings and outputs in Rmarkdown {https://t.co/Snxd04FKQ2} #rstats #DataScience
— R-bloggers (@Rbloggers) January 21, 2022
Finally understanding what “statistical significance” and p-values mean: A simple example (w {https://t.co/MsbbkgSlDk} #rstats #DataScience
— R-bloggers (@Rbloggers) January 9, 2022
Using bayesian optimisation to tune a XGBOOST model in R {https://t.co/fXXU4DMaEe} #rstats #DataScience
— R-bloggers (@Rbloggers) January 8, 2022
Tips for building a Twitter bot with R and Github Actions {https://t.co/FTrKW1S0zL} #rstats #DataScience
— R-bloggers (@Rbloggers) January 16, 2022
A package of Machine Learning datasets has arrived for R – MLDataR {https://t.co/VUSqbrTFem} #rstats #DataScience
— R-bloggers (@Rbloggers) January 5, 2022
Top 7 Best R Shiny Books and Courses That Are Completely Free {https://t.co/v8JBTXbhPr} #rstats #DataScience
— R-bloggers (@Rbloggers) January 6, 2022
Introduction to Geospatial Visualization with the tmap package {https://t.co/fPasXDp9jb} #rstats #DataScience
— R-bloggers (@Rbloggers) December 31, 2021
New Book on Machine Learning {https://t.co/Qn1knpQWTC} #rstats #DataScience
— R-bloggers (@Rbloggers) December 23, 2021
Binary image classification using Keras in R: Using CT scans to predict patients with Covid {https://t.co/PZTKZC9TSu} #rstats #DataScience
— R-bloggers (@Rbloggers) January 2, 2022
How To Connect R Shiny to Postgres Database – The Definite Guide {https://t.co/RXkj93s8IF} #rstats #DataScience
— R-bloggers (@Rbloggers) January 11, 2022
Using databases with Shiny {https://t.co/Og4tMdVVzF} #rstats #DataScience
— R-bloggers (@Rbloggers) January 2, 2022
How to install (and update!) R and RStudio {https://t.co/kTyBGRUcUi} #rstats #DataScience
— R-bloggers (@Rbloggers) January 1, 2022
A new way to discover R Programming books! {https://t.co/E4tnFF6ZHz} #rstats #DataScience
— R-bloggers (@Rbloggers) January 9, 2022
Handling Categorical Data in R – Part 1 {https://t.co/fips2do8sU} #rstats #DataScience
— R-bloggers (@Rbloggers) January 7, 2022
---
title: "RBloggers Top Tweets"
output:
flexdashboard::flex_dashboard:
vertical_layout: scroll
source_code: embed
theme:
version: 4
bootswatch: yeti
css: styles/main.css
---
```{r setup, include=FALSE}
library(flexdashboard)
library(dplyr)
library(httr)
library(lubridate)
library(jsonlite)
library(purrr)
rbloggers <- fromJSON("data/rbloggers.json")
get_tweet_embed <- function(user, status_id) {
url <-
stringr::str_glue(
"https://publish.twitter.com/oembed?url=https://twitter.com/{user}/status/{status_id}&partner=&hide_thread=false"
)
response <- GET(url) %>%
content()
return(shiny::HTML(response$html))
}
```
Column {.tabset .tabset-fade}
-----------------------------------------------------------------------
### Top Tweets - 7 days {.tweet-wall}
```{r}
rblog_7 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 7, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_7_html <-
map2_chr(rblog_7$screen_name, rblog_7$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_7_html}"))
```
### Top Tweets - 30 days {.tweet-wall}
```{r}
rblog_30 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 30, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_30_html <-
map2_chr(rblog_30$screen_name, rblog_30$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_30_html}"))
```